Unmanned vehicle cross-medium attitude control method

Abstract

The invention belongs to the technical field of unmanned vehicle control methods, and particularly relates to an unmanned vehicle cross-medium attitude control method. Comprising the following steps: establishing a coordinate system and a transformation matrix thereof, establishing a reference coordinate system and a transformation matrix thereof according to an earth coordinate system and the position of the vehicle, establishing a six-degree-of-freedom equation of the unmanned vehicle under the body coordinate system, and establishing a vehicle single-medium motion state control system model; defining aircraft flight state variables, and obtaining an aircraft motion state control system model based on the definition; establishing an aircraft cross-medium motion state control system model, and optimizing aircraft single-medium motion control based on expected flight state variables. The method is mainly suitable for analyzing and controlling the motion states of various cross-medium unmanned aerial vehicles, mainly submarine-launched unmanned aerial vehicles and water-air dual-purpose unmanned aerial vehicles, and is used for simplifying the complexity of a control scheme in a complex motion state and improving the control efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned vehicle control methods, and particularly relates to an unmanned vehicle cross-medium attitude control method. Background Art

[0002] A multi-medium unmanned vehicle refers to a vehicle that can navigate in different media and provide more diverse functions. During the flight of the above vehicle, it involves various motion states between different media and at the media interfaces. Effective analysis and control of these motion states are necessary conditions for completing the control of the vehicle's navigation, operation actions, and other contents. Summary of the Invention

[0003] The purpose of the present invention is to provide an unmanned vehicle cross-medium attitude control method applicable to multi-medium unmanned vehicles for realizing the analysis and control of their cross-medium motion states based on actual requirements.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions.

[0005] An unmanned vehicle cross-medium attitude control method includes the following steps:

[0006] Step 1: Establish a coordinate system and its transformation matrix. Based on the Earth coordinate system and the position of the vehicle itself, establish a reference coordinate system and its transformation matrix. The reference coordinate system includes the Earth coordinate system O e X e Y e Z e and the body coordinate system O b X b Y b Z b ; Based on the coordinate system and the attitude angle vector of the unmanned aerial vehicle Establish a rotation matrix b X b Y b Z b from the body coordinate system O e X e Y e Z e to the Earth coordinate system O

[0007] Step 2: Establish the six-degree-of-freedom equation of the unmanned vehicle under the body coordinate system O b X b Y b Z b , expressed as:

[0008]

[0009] f 外 = G + fliu +f pi +f μ +f C

[0010] t 外 =t G +t liu +t pi +t μ +t C

[0011] where v 1 =[u, v, w] T represents the three-axis linear velocity matrix, v 2 =[p, q, r] T represents the three-axis angular velocity matrix, m s is the mass of the vehicle, r s is the coordinate of the vehicle's center of mass in the body coordinate system, I s represents the vehicle's inertia tensor, f 外 refers to the resultant external force acting on the vehicle, f 内 refers to the internal force of the vehicle, t 外 refers to the external torque, t 内 refers to the internal torque; G represents gravity, t G represents the gravity torque; f liu represents the fluid inertia force; t liu represents the fluid inertia force torque; f pi represents the fluid buoyancy, t pi represents the fluid buoyancy torque, r pi represents the fluid buoyancy moment arm; f μ represents the fluid buoyancy resistance, t μ represents the fluid buoyancy resistance torque; f c represents the thrust of the power system, t μ represents the thrust torque of the power system; represents the roll angle of the vehicle, θ represents the pitch angle of the vehicle, ψ represents the yaw angle of the vehicle;

[0012] Step 3, establish the single-medium motion state control system model of the vehicle

[0013] Define the vehicle flight state variables x i,1 and x i,2 , where i = 1, 2... 4, x 1,1 represents the flight altitude of the vehicle, x 3,1 =θ, x 4,1 =ψ, x 1,2 =w, x 2,2 =p, x 3,2 =q, x 4,2 =r;

[0014] Based on the above definitions, the motion state control system model of the vehicle can be expressed as

[0015]

[0016] where represents the corresponding variable control function of the vehicle's non-linear system, represents the vehicle's state variables and represents the time-varying parameter vector; b i (t) is the time-varying coefficient, and u i is the control output of the vehicle's power system acting on the corresponding variables;

[0017] Step 4: Establish the cross-medium motion state control system model of the vehicle

[0018] Based on the degree-of-freedom equations of the unmanned vehicle under the body coordinate system O b X b Y b Z b the cross-medium motion state control system model of the vehicle is established and can be expressed as:

[0019]

[0020] During the cross-medium motion process, the vehicle is in two different medium spaces. The external forces and external torques of its system can be calculated separately in different medium intervals;

[0021] Among them, the fluid buoyancy f pi will change rapidly as it quickly passes through the medium interface, making it difficult to accurately analyze. Considering that the cross-medium motion speed is fast, the process takes a short time, and the buoyancy in the air can be ignored compared to the buoyancy in the liquid, the fluid buoyancy and the fluid buoyancy moment are calculated based on the draft depth of the vehicle during cross-medium motion;

[0022] Suppose the vertical heights of the vehicle's center of mass when it reaches and passes through the medium interface under the body coordinate system are z 1 and z 2 , respectively. Then, the buoyancy f pi and the buoyancy moment t pi acting on the vehicle can be transformed into piecewise functions with respect to the vertical height of its center of mass and can be expressed as

[0023]

[0024] ρ is the density of the medium in the space where the vehicle is located, and V 排 is the volume of the liquid displaced by the vehicle;

[0025] t pi = gr (η, z) × f pi ; where g r (η, z) is a fitting function of the buoyancy moment and the perpendicular height of the centroid obtained by experimental induction; where is the inclination angle of the vehicle during the cross-medium movement;

[0026] Step 5. Optimization of the single-medium motion control of the vehicle based on the desired flight state variables

[0027] Based on the flight state variables x of the vehicle i,1 Define the desired flight state variables x i,1+ , representing the expected value of the state variable x i,1 ; From the flight state variables x of the vehicle i,1 and its desired flight state variables x i,1+ , the first-level state error Δx of the vehicle control system is obtained i = x i,1 - x i,1+ ;

[0028] is the control system state error, and define the first-level error design variable

[0029]

[0030] where X i = (g i0 - g i∞ ) e -git + g i∞ is the error constraint function; g i,1 , g i,2 , g i0 , g i∞ , g i are the error design parameters;

[0031] Derive the error design variable e i,1 to obtain the control model for the first-level error design variable

[0032]

[0033] Based on the above error design variable control model, the controller for controlling the vehicle speed error can be expressed as:

[0034]

[0035] where c i is the speed error control coefficient greater than zero;

[0036] The control parameter x i,2d actually refers to the expected trajectory of the vehicle speed state quantity curve;

[0037] Process the control parameter x using a first-order filter i,2d to reduce complexity and obtain the velocity layer control quantity of the vehicle motion state control system model where μ i is the filter time constant greater than zero;

[0038] Based on the velocity layer control quantity and the velocity variable x i,2 obtain the secondary state error of the vehicle control system

[0039] Based on the secondary state error Δx of the vehicle control system i,2 =[Δx 1,2 , Δx 2,2 , Δx 3,2 , Δx 4,2 , define the secondary error variable e of the vehicle control system f =[Δx 1,2 , Δx 2,2 , Δx 3,2 , Δx 4,2 T ;

[0040] Establish a controller for the secondary error variable of the vehicle control system

[0041] where u f =[u 1 , u 2 , u 3 , u 4 T ; B(t)=diag[b 1 (t), b 2 (t), b 3 (t), b 4 (t)] T .

[0042] For further improvement or specific implementation of the above-mentioned cross-media attitude control method for an unmanned vehicle, the Earth coordinate system O e X e Y e Z e Taking the starting position of the vehicle as the coordinate origin O e , with the due north direction as the O e X e axis, with the due east direction as the O e Y e axis, and with the direction perpendicular to O e X e ​​Y e Plane and vertically downward as O e Z e axis is established; the body coordinate system O b X b Y b Z b Taking the aircraft body coordinate as the coordinate origin O b and the initial motion direction of the aircraft as O b X b axis, with O e Z e axis in the opposite direction as O b Z b axis, and the direction perpendicular to O b X b Z b and forming a right - hand system with O b X b axis and O b Z b axis is O b Y b axis.

[0043] For the further improvement or specific implementation of the aforementioned cross - medium attitude control method of the unmanned vehicle, the rotation matrix from the body coordinate system O b X b Y b Z b to the earth coordinate system O e X e Y e Z e is as

[0044]

[0045] For the further improvement or specific implementation of the aforementioned cross - medium attitude control method of the unmanned vehicle, where G = m s g, t G = r s ×G; M(l) refers to the added mass matrix of the vehicle; Table, C(v 1 , v 2 ) refers to the Coriolis matrix; f pi = ρV 排 g, t pi = r pi f pi , r pi represents the fluid buoyancy moment arm;

[0046]

[0047] where V is the vehicle velocity vector, S is the cross-sectional area of the vehicle; L w is the equivalent arm of the fluid resistance, α is the angle of attack, and β is the sideslip angle; are the dimensionless angular velocities in the body coordinate system; where represents the hydrodynamic coefficient in each direction determined based on the three axes of the body coordinate system, represents the hydrodynamic moment coefficient in each direction determined based on the body coordinate system, and |* represents the normal vector of the motion direction or the unit vector perpendicular to the motion direction and pointing in the opposite direction of the vehicle's motion direction. Description of the Drawings

[0048] Figure 1 is a schematic flow chart of the cross-media attitude control method for an unmanned vehicle. Detailed Embodiment

[0049] The present invention will be described in detail below with reference to specific embodiments.

[0050] The present invention relates to a cross-media attitude control method for an unmanned vehicle, which is mainly applicable to various cross-media unmanned aerial vehicles, mainly submersible unmanned aerial vehicles and amphibious unmanned aerial vehicles for analyzing and controlling the motion states, aiming to simplify the complexity of the control scheme under complex motion states and improve the control efficiency. The main process is as Figure 1 shown.

[0051] The cross-media attitude control method for the unmanned vehicle of the present invention mainly includes the following steps:

[0052] By establishing the earth coordinate system and the body coordinate system as the analysis basis for various motion states and parameters, necessary conditions are provided for subsequent operation and analysis;

[0053] Combined with the kinetic theory and the degree-of-freedom equation, a corresponding mathematical model of the motion state of the unmanned vehicle in the medium is established to create a basic theoretical analysis basis during the motion process;

[0054] Based on the nonlinear control theory and its mathematical model, a control process model of the unmanned submersible control system under different motion states is established to weaken the continuous influence of real-time dynamic parameters on the uncertainty of the motion state; a scheme for optimizing the control effect of the unmanned submersible control system and reducing the final error is established based on the designable error variables starting from the results.

[0055] The following are the specific step contents:

[0056] Step 1: Establish a coordinate system and its transformation matrix. According to the earth coordinate system and the position of the vehicle itself, a reference coordinate system and its transformation matrix are established. The reference coordinate system includes the earth coordinate system O e X e Y e Z eand the body coordinate system O b X b Y b Z b ;

[0057] In this application, the earth coordinate system O e X e Y e Z e Taking the departure position of the vehicle as the coordinate origin O e , with the due north direction as the O e X e axis, with the due east direction as the O e Y e axis, and with the direction perpendicular to the O e X e Y e plane and vertically downward as the O e Z e axis is established; the body coordinate system O b X b Y b Z b Taking the body coordinate of the vehicle as the coordinate origin O b , with the initial movement direction of the vehicle as the O b X b axis, with the direction opposite to the O e Z e axis as the O b Z b axis, and with the direction perpendicular to the O b X b Z b and forming a right - hand system with the O b X b axis and the O b Z b axis as the O b Y b axis;

[0058] Based on the foregoing coordinate systems and the attitude angle vector of the UAV A rotation matrix from the body coordinate system O b X b Y b Z b to the earth coordinate system O e X e Y e Z e is established

[0059]

[0060] where represents the roll angle of the vehicle, θ represents the pitch angle of the vehicle, and ψ represents the yaw angle of the vehicle;

[0061] Step 2. Establish the body coordinate system O b X b Y b Z b The six-degree-of-freedom equation of the underwater unmanned vehicle can be expressed as

[0062]

[0063] f 外 =G + f liu + f pi + f μ + f C

[0064] t 外 =t G + t liu + t pi + t μ + t C

[0065] where v 1 =[u, v, w] T represents the three-axis linear velocity matrix, and v 2 =[p, q, r] T represents the three-axis angular velocity matrix, m s is the mass of the vehicle, r s is the coordinate of the vehicle's center of mass in the body coordinate system, I s represents the vehicle's inertia tensor, f 外 refers to the resultant external force acting on the vehicle, f 内 refers to the internal force of the vehicle, t 外 refers to the external torque, t 内 refers to the internal torque; G = m s g represents the gravitational force, t G =r s ×G represents the gravitational torque; represents the fluid inertia force, and M(l) refers to the added mass matrix of the vehicle; represents the fluid inertia torque, C(v 1 , v 2 ) refers to the Coriolis matrix; f pi =ρV 排 g represents the fluid buoyancy force, t pi =r pi f pi represents the fluid buoyancy torque, and r pi represents the fluid buoyancy force arm;

[0066] where represents the fluid buoyancy resistance, represents the fluid buoyancy resistance torque; fc Denote the thrust of the power system as \(t\) μ Denote the thrust moment of the power system;

[0067] where \(\rho\) is the density of the medium in the space where the vehicle is located, \(V\) 排 is the volume of the liquid displaced by the vehicle, \(V\) is the velocity vector of the vehicle, \(S\) is the cross-sectional area of the vehicle, \(L\) w is the equivalent arm of the fluid resistance, \(\alpha\) is the angle of attack, and \(\beta\) is the sideslip angle; are the dimensionless angular velocities in the body coordinate system respectively; where Denote the hydrodynamic coefficients in each direction determined based on the three axes of the body coordinate system, Denote the hydrodynamic moment coefficients in each direction determined based on the body coordinate system, \(|\cdot|\) represents the normal vector of the motion direction or the unit vector perpendicular to the motion direction and pointing in the opposite direction of the vehicle's motion direction;

[0068] Step 3: Establish the single-medium motion state control system model of the vehicle

[0069] Define the flight state variables \(x\) i,1 and \(x\) i,2 , where \(i = 1, 2,\cdots, 4\), \(x\) 1,1 represents the flight altitude of the vehicle, \(x\) 3,1 =\(\theta\), \(x\) 4,1 =\(\psi\), \(x\) 1,2 =\(w\), \(x\) 2,2 =\(p\), \(x\) 3,2 =\(q\), \(x\) 4,2 =\(r\);

[0070] Based on the above definitions, the motion state control system model of the vehicle can be expressed as

[0071]

[0072] where Denote the corresponding variable control function of the vehicle's nonlinear system, Denote the state variables of the vehicle and Denote the time-varying parameter vector; \(b\) i (t) is the time-varying coefficient, \(u\) i is the control output of the vehicle's power system acting on the corresponding variable;

[0073] Step 4: Establish the cross-medium motion state control system model of the vehicle

[0074] Based on the body coordinate system \(O\) b \(X\) b \(Y\) b \(Z\) bThe degree-of-freedom equations of the underwater unmanned vehicle are used to establish the control system model of the vehicle's cross-medium motion state, which can be expressed as:

[0075]

[0076] During the cross-medium motion process, the vehicle is located in two different medium spaces. The external forces and external torques of its system can be calculated separately in different medium intervals;

[0077] Among them, the fluid buoyancy f pi will change rapidly as it quickly passes through the medium interface, making it difficult to accurately analyze. Considering that the cross-medium motion speed is relatively fast, the process takes a short time, and the buoyancy in the air can be ignored compared to the buoyancy in the liquid, the fluid buoyancy and the fluid buoyancy moment are calculated based on the draft depth of the vehicle during cross-medium motion;

[0078] Suppose the vertical heights of the center of mass of the vehicle when it reaches and passes through the medium interface in the body coordinate system are z 1 and z 2 , respectively. Then the buoyancy f pi and the buoyancy moment t pi acting on the vehicle can be transformed into piecewise functions of its vertical height of the center of mass, which can be expressed as

[0079]

[0080] t pi = g r (η, z) × f pi ; where g r (η, z) is the fitting function of the buoyancy moment and the vertical height of the center of mass obtained by experimental induction; where is the inclination angle of the vehicle during the cross-medium motion process;

[0081] Step 5. Optimization of the single-medium motion control of the vehicle based on the desired flight state variables

[0082] Based on the flight state variables x i,1 of the vehicle, the desired flight state variables x i,1+ are defined, representing the expected values of the state variables x i,1 ; From the flight state variables x i,1 of the vehicle and its desired flight state variables x i,1+ , the first-level state error Δx i of the vehicle control system is obtained as Δx i,1 = x i,1+ - x

[0083] is the state error of the control system, and the first-level error design variables are defined

[0084]

[0085] where is the error constraint function; g i,1 、g i,2 、g i0 、g i∞ 、g i are error design parameters;

[0086] Derive the derivative with respect to the error design variable e i,1 to obtain the control model for the first-level error design variables

[0087]

[0088] Based on the above error design variable control model, the controller for controlling the speed error of the vehicle can be expressed as:

[0089]

[0090] where c i is the speed error control coefficient greater than zero;

[0091] The control parameter x i,2d actually refers to the desired trajectory of the vehicle speed state quantity curve;

[0092] Use a first-order filter to process the control parameter x i,2d to reduce the complexity and obtain Obtain the speed layer control quantity of the vehicle motion state control system model where μ i is the filter time constant greater than zero;

[0093] Based on the speed layer control quantity and the speed variable x i,2 obtain the secondary state error of the vehicle control system

[0094] Based on the secondary state error Δx of the vehicle control system i,2 =[Δx 1,2 ,Δx 2,2 ,Δx 3,2 ,Δx 4,2 , define the secondary error variable e of the vehicle control system f =[Δx 1,2 ,Δx 2,2 ,Δx 3,2 ,Δx 4,2 T ;

[0095] Establish the secondary error variable controller of the vehicle control system ​

[0096] wherein u f =[u 1 ,u 2 ,u 3 ,u 4 T ; B(t) = diag[b 1 (t), b 2 (t), b 3 (t), b 4 (t)] T ;

[0097] In this application, through the parametric optimization design of the control system for controlling errors, the real control error of the system is converted into control coefficients and control parameters. Through the verification of stability theory, it can be confirmed that the corresponding controller and control parameters can ensure that effective values with control significance can be obtained under the corresponding control system, thereby avoiding the interference of the real control parameters of multiple parameters.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting the protection scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the essence and scope of the technical solutions of the present invention.​

Claims

1. A method for controlling the attitude of an unmanned aerial vehicle across a medium, characterized in that: The steps include: Step 1: Establish a coordinate system and its conversion matrix. Establish a reference coordinate system and its conversion matrix based on the earth coordinate system and the position of the aircraft. The reference coordinate system includes the earth coordinate system. e X e Y e Z e And the body coordinate system O b X b Y b Z b ; Based on the coordinate system and the drone attitude angle vector Establish the body coordinate system O b X b Y b Z b To the Earth coordinate system O e X e Y e Z e The rotation matrix Step 2: Establish the body coordinate system O b X b Y b Z b The six-degree-of-freedom equation of the unmanned aerial vehicle is expressed as: f 外 =G+f liu +f pi +f μ +f C t 外 =t G +t liu +t pi +t μ +t C where v1 = [u, v, w] T Represents the three-axis velocity matrix, v2 = [p, q, r] T Represents the three-axis angular velocity matrix, m s is the mass of the spacecraft, r s is the coordinate of the center of mass of the vehicle in the body coordinate system, I s represents the vehicle inertia tensor, f 外 refers to the total external force on the spacecraft, f 内 refers to the internal force of the spacecraft, t 外 refers to the external torque, t 内 refers to the internal torque; G represents gravity, t G represents the gravitational moment; f liu represents the fluid inertia force; t liu represents the dynamic moment of inertia of the fluid; f pi represents the fluid buoyancy, t pi represents the fluid buoyancy moment, r pi represents the buoyancy arm of the fluid; f μ represents the fluid buoyancy resistance, t μ represents the fluid buoyancy drag moment; f c represents the power system thrust, t μ It represents the thrust torque of the power system; represents the roll angle of the aircraft, θ represents the pitch angle of the aircraft, and ψ represents the yaw angle of the aircraft; Step 3: Establish a single-medium motion state control system model for the aircraft Define the aircraft flight state variable x i,1 and x i,2 , where i = 1, 2...4, x 1,1 Indicates the flight altitude of the aircraft, x 3,1 =θ,x 4,1 =ψ,x 1,2 =w,x 2,2 =p,x 3,2 =q,x 4,2 = r; Based on the above definition, the vehicle motion state control system model can be expressed as in represents the corresponding variable control function of the nonlinear system of the spacecraft, represents the state of the aircraft and represents the time-varying parameter vector; b i (t) is the time-varying coefficient, u i It is the control output of the vehicle power system acting on the corresponding variables; Step 4: Establish a control system model for the vehicle's cross-medium motion state Based on the body coordinate system O b X b Y b Z b The degree of freedom equation of the unmanned aerial vehicle is obtained, and the model of the aerial vehicle cross-medium motion state control system is established, which can be expressed as: During the cross-medium motion, the spacecraft is located in two different medium spaces, and the external forces and torques of the system can be calculated separately in different medium intervals; The fluid buoyancy f pi It will change rapidly as it passes through the medium interface, making it difficult to analyze accurately. Considering that the speed of movement across the medium is fast, the process takes a short time, and the buoyancy in the air is negligible relative to the buoyancy in the liquid, the fluid buoyancy and fluid buoyancy distance are calculated based on the draft of the vehicle when it moves across the medium. Assuming that the vertical heights of the center of mass of the spacecraft when it reaches and passes through the medium interface in the body coordinate system are z1 and z2 respectively, the buoyancy f on the spacecraft can be calculated as pi and buoyancy distance t pi Transformed into a phase function about the vertical height of its center of mass, it can be expressed as ρ is the medium density of the space where the spacecraft is located, V 排 is the volume of fluid discharged by the aircraft; t pi =g r (η,z)×f pi ; where g r (η,z) is the fitting function of the buoyancy distance and the vertical height of the center of mass obtained by experimental induction; is the inclination angle of the body during the movement across the medium; Step 5: Optimization of single-medium motion control of aircraft based on expected flight state variables Based on the aircraft flight state variable x i,1 Define the expected flight state variable x i,1+ , which means the state variable x i,1 Expected value; The aircraft flight state variable x i,1 and its expected flight state variable x i,1+ , and obtain the first-level state error Δx of the vehicle control system i =x i,1 -x i,1+ ; To control the state error of the system, define the first-level error design variable in is the error constraint function; g i,1 , g i,2 , g i0 , g i∞ , g i is the error design parameter; For the error design variable e i,1 Derivative, get the control model of the first-order error design variable The controller for controlling the speed error of the aircraft based on the above error design variable control model can be expressed as: where c i is the speed error control coefficient greater than zero; Control parameter x i,2d It actually refers to the expected trajectory of the vehicle's velocity state curve; Use a first-order filter to control the parameter x i,2d Processing to reduce complexity Get the velocity layer control quantity of the aircraft motion state control system model where μ i is the filter time constant greater than zero; Based on the speed layer control and the speed variable x i,2 Get the secondary state error of the vehicle control system Based on the secondary state error Δx of the vehicle control system i,2 =[Δx 1,2 ,Δx 2,2 ,Δx 3,2 ,Δx 4,2 ], define the secondary error variable e of the vehicle control system f =[Δx 1,2 ,Δx 2,2 ,Δx 3,2 ,Δx 4,2 ] T ; Establishing a Secondary Error Variable Controller for Vehicle Control Systems in u f =[u1,u2,u3,u4] T ;B(t)=diag[b1(t),b2(t),b3(t),b4(t)] T .

2. The cross-medium attitude control method for an unmanned aerial vehicle according to claim 1, characterized in that: The earth coordinate system O e X e Y e Z e The origin of the coordinate system is O. e , with due north as O e X e Axis, with due east direction as O e Y e Axis, perpendicular to O e X e Y e Flat and vertical downward is O e Z e Axis establishment; body coordinate system O b X b Y b Z b The coordinates of the aircraft body are taken as the coordinate origin O b , with the initial motion direction of the spacecraft as O b X b Axis, O e Z e The opposite direction of the axis is O b Z b Axis, perpendicular to O b X b Z b And with O b X b Axis and O b Z b The direction of the right-handed system is O. b Y b axis.

3. The cross-medium attitude control method for an unmanned aerial vehicle according to claim 1, characterized in that: From the body coordinate system O b X b Y b Z b To the Earth coordinate system O e X e Y e Z e The rotation matrix for 4. The cross-medium attitude control method for an unmanned aerial vehicle according to claim 1, characterized in that: Where G = m s g,t G =r s ×G; M(l) refers to the vehicle additional mass matrix; table, C(v1,v2) refers to the Coriolis matrix; f pi =ρV 排 g,t pi =r pi f pi , r pi represents the fluid buoyancy arm; Where V is the aircraft velocity vector, S is the aircraft cross-sectional area; L w is the equivalent force arm of fluid resistance, α is the angle of attack, and β is the sideslip angle; are the dimensionless angular velocities in the body coordinate system respectively; It represents the fluid dynamic coefficients in each direction determined based on the three-axis directions of the body coordinate system. represents the fluid dynamic moment coefficient in each direction determined based on the body coordinate system, and |* represents the normal vector in the direction of motion or the unit vector perpendicular to the direction of motion and pointing in the opposite direction of the vehicle's motion.

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